25,087 research outputs found
Robust Temporally Coherent Laplacian Protrusion Segmentation of 3D Articulated Bodies
In motion analysis and understanding it is important to be able to fit a
suitable model or structure to the temporal series of observed data, in order
to describe motion patterns in a compact way, and to discriminate between them.
In an unsupervised context, i.e., no prior model of the moving object(s) is
available, such a structure has to be learned from the data in a bottom-up
fashion. In recent times, volumetric approaches in which the motion is captured
from a number of cameras and a voxel-set representation of the body is built
from the camera views, have gained ground due to attractive features such as
inherent view-invariance and robustness to occlusions. Automatic, unsupervised
segmentation of moving bodies along entire sequences, in a temporally-coherent
and robust way, has the potential to provide a means of constructing a
bottom-up model of the moving body, and track motion cues that may be later
exploited for motion classification. Spectral methods such as locally linear
embedding (LLE) can be useful in this context, as they preserve "protrusions",
i.e., high-curvature regions of the 3D volume, of articulated shapes, while
improving their separation in a lower dimensional space, making them in this
way easier to cluster. In this paper we therefore propose a spectral approach
to unsupervised and temporally-coherent body-protrusion segmentation along time
sequences. Volumetric shapes are clustered in an embedding space, clusters are
propagated in time to ensure coherence, and merged or split to accommodate
changes in the body's topology. Experiments on both synthetic and real
sequences of dense voxel-set data are shown. This supports the ability of the
proposed method to cluster body-parts consistently over time in a totally
unsupervised fashion, its robustness to sampling density and shape quality, and
its potential for bottom-up model constructionComment: 31 pages, 26 figure
Grasping and Control Issues in Adaptive End Effectors
Research into robotic grasping and manipulation has led to the development of a large number of tendon based end effectors. Many are, however, developed as a research tool, which are limited in application to the laboratory environment. The main reason being that the designs requiring a large number of actuators to be controlled. Due to the space and safety requirements, very few have been developed and commissioned for industrial applications. This paper presents design of a rigid link finger operated by a minimum number of actuators, which may be suitable for a number of adaptive end effectors. The adaptive nature built into the end effector (due to limited number of actuators) presents considerable problems in grasping and control. The paper discusses the issues associated with such designs. The research can be applicable to any adaptive end effectors that are controlled by limited number of actuators and evaluates their suitability in industrial environments
A finger mechanism for adaptive end effectors
This paper presents design and analysis of a rigid link finger, which may be suitable for a number of adaptive end effectors. The design has evolved from an industrial need for a tele-operated system to be used in nuclear environments. The end effector is designed to assist repair work in nuclear reactors during retrieval operation, particularly for the purpose of grasping objects of various shape, size and mass. The work is based on the University of Southampton's Whole Arm Manipulator, which has a special design consideration for safety and flexibility. The paper discusses kinematic issues associated with the finger design, and to the end of the paper specifies the limits of finger operating parameters for implementing control law
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